Datasets:

maxie-12321
/

schedula-data

license: mit
task_categories:
  - text2text-generation
tags:
  - scheduler
  - text-to-json
  - tagalog
  - taglish
  - synthetic
  - from-scratch
size_categories:
  - 100K<n<1M

Schedula dataset

Fully synthetic, seeded, reproducible corpus for training Schedula - a tiny from-scratch model that turns messy natural language (English / Taglish / Filipino) into structured schedule JSON.

Modes

mode	input	output
`event_extract`	sentences, bullet dumps, decorated announcements (unicode stars/stylized headers), edit statements; embedded schedule JSON must be ignored	`{"events":[{title, category, date, start_time, duration_min, location, priority}]}`
`duplicate_detect`	CURRENT LIST json (+ optional `"time_created": "... ##ignore"` metadata) + numbered NEW ITEMS (1-8)	`{"verdicts":[{duplicate, match_id, confidence, reason}]}`

Conventions

<today> anchor date resolves every relative expression ("next week tue", "bukas", "sa loob ng 2 linggo").
Fields suffixed ##ignore are app-owned metadata: present in inputs, never copied to outputs.
Items under "daily reminders"-style headers are undated (null) by design.
Category labels come from the per-example schema hint (default enum plus alternate English/Tagalog sets) so the model learns hint-driven mapping.
Duplicate boundaries include numbered schoolwork (quiz #2 vs quiz #3 never match) and EN<->Filipino translation pairs (do match).

Splits

{ "train": { "duplicate_detect": 1282, "event_extract": 2718 }, "val": { "duplicate_detect": 184, "event_extract": 416 }, "test": { "duplicate_detect": 174, "event_extract": 426 } }

Robustness noise (typos/filler/casing) appears only in val/test (16%).

Reproducibility

Built by python -m schedula.data.build --config configs/default.yaml (seed 1337, created 2026-08-24). The generator lives at https://github.com/maxie-12321/schedula